A survey of recommendation techniques based on offline data processing

Ren, Yongli, Li, Gang and Zhou, Wanlei 2015, A survey of recommendation techniques based on offline data processing, Concurrency computation: practice and experience, vol. 27, no. 15, pp. 3915-3942, doi: 10.1002/cpe.3370.

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Title A survey of recommendation techniques based on offline data processing
Author(s) Ren, Yongli
Li, GangORCID iD for Li, Gang orcid.org/0000-0003-1583-641X
Zhou, WanleiORCID iD for Zhou, Wanlei orcid.org/0000-0002-1680-2521
Journal name Concurrency computation: practice and experience
Volume number 27
Issue number 15
Start page 3915
End page 3942
Total pages 28
Publisher Wiley
Place of publication London, Eng.
Publication date 2015-10
ISSN 1532-0626
Keyword(s) Science & Technology
Computer Science, Software Engineering
Computer Science, Theory & Methods
Computer Science
collaborative filtering
recommender systems
Summary Recommendations based on offline data processing has attracted increasing attention from both research communities and IT industries. The recommendation techniques could be used to explore huge volumes of data, identify the items that users probably like, translate the research results into real-world applications and so on. This paper surveys the recent progress in the research of recommendations based on offline data processing, with emphasis on new techniques (such as temporal recommendation, graph-based recommendation and trust-based recommendation), new features (such as serendipitous recommendation) and new research issues (such as tag recommendation and group recommendation). We also provide an extensive review of evaluation measurements, benchmark data sets and available open source tools. Finally, we outline some existing challenges for future research.
Language eng
DOI 10.1002/cpe.3370
Field of Research 0805 Distributed Computing
0803 Computer Software
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Wiley
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081077

Document type: Journal Article
Collection: School of Information Technology
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